{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\research\works\주제45_계엄_탄핵_민주주의\democratization\data\code_q2_q3.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 4 May 2025, 23:56:25

{com}. ologit ImpeachmentSupport PastMartialLawsJustified Age Gender Income Education Religion Position

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-2756.2672}  
Iteration 1:{space 3}log likelihood = {res:-1665.6886}  
Iteration 2:{space 3}log likelihood = {res:-1415.0489}  
Iteration 3:{space 3}log likelihood = {res:-1361.0349}  
Iteration 4:{space 3}log likelihood = {res:-1348.1001}  
Iteration 5:{space 3}log likelihood = {res:-1345.5624}  
Iteration 6:{space 3}log likelihood = {res:-1345.0182}  
Iteration 7:{space 3}log likelihood = {res:-1344.8892}  
Iteration 8:{space 3}log likelihood = {res:-1344.8603}  
Iteration 9:{space 3}log likelihood = {res:-1344.8539}  
Iteration 10:{space 2}log likelihood = {res:-1344.8529}  
Iteration 11:{space 2}log likelihood = {res:-1344.8528}  
Iteration 12:{space 2}log likelihood = {res:-1344.8528}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     2,000
{txt}{col 49}LR chi2({res}7{txt}){col 67}= {res}   2822.83
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1344.8528{txt}{col 49}Pseudo R2{col 67}= {res}    0.5121

{txt}{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      ImpeachmentSupport{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      z{col 58}   P>|z|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
PastMartialLawsJustified {c |}{col 26}{res}{space 2}-.3685889{col 38}{space 2} .0581382{col 49}{space 1}   -6.34{col 58}{space 3}0.000{col 66}{space 4}-.4825375{col 79}{space 3}-.2546402
{txt}{space 21}Age {c |}{col 26}{res}{space 2} -.082255{col 38}{space 2} .0564001{col 49}{space 1}   -1.46{col 58}{space 3}0.145{col 66}{space 4} -.192797{col 79}{space 3} .0282871
{txt}{space 18}Gender {c |}{col 26}{res}{space 2}  -.00136{col 38}{space 2} .0923665{col 49}{space 1}   -0.01{col 58}{space 3}0.988{col 66}{space 4}-.1823951{col 79}{space 3} .1796751
{txt}{space 18}Income {c |}{col 26}{res}{space 2}-.1607134{col 38}{space 2} .0726028{col 49}{space 1}   -2.21{col 58}{space 3}0.027{col 66}{space 4}-.3030123{col 79}{space 3}-.0184145
{txt}{space 15}Education {c |}{col 26}{res}{space 2}-.0018316{col 38}{space 2} .0727833{col 49}{space 1}   -0.03{col 58}{space 3}0.980{col 66}{space 4}-.1444843{col 79}{space 3} .1408212
{txt}{space 16}Religion {c |}{col 26}{res}{space 2}-.0523328{col 38}{space 2} .1060594{col 49}{space 1}   -0.49{col 58}{space 3}0.622{col 66}{space 4}-.2602054{col 79}{space 3} .1555399
{txt}{space 16}Position {c |}{col 26}{res}{space 2} 38.75516{col 38}{space 2}  876.741{col 49}{space 1}    0.04{col 58}{space 3}0.965{col 66}{space 4}-1679.626{col 79}{space 3} 1757.136
{txt}{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                   /cut1 {c |}{col 26}{res}{space 2}-1.765383{col 38}{space 2} .3615741{col 66}{space 4}-2.474055{col 79}{space 3} -1.05671
{txt}                   /cut2 {c |}{col 26}{res}{space 2} 17.63248{col 38}{space 2} 609.0101{col 66}{space 4}-1176.005{col 79}{space 3}  1211.27
{txt}                   /cut3 {c |}{col 26}{res}{space 2} 37.42661{col 38}{space 2} 876.7411{col 66}{space 4}-1680.954{col 79}{space 3} 1755.808
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estimates store model_1

. 
. 
. 
. 
. 
. ologit MartialLawLimitsDemocracy PastMartialLawsJustified Age Gender Income Education Religion Position

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-3183.4903}  
Iteration 1:{space 3}log likelihood = {res:-2208.0282}  
Iteration 2:{space 3}log likelihood = {res: -2056.685}  
Iteration 3:{space 3}log likelihood = {res:-2040.1582}  
Iteration 4:{space 3}log likelihood = {res:-2039.6402}  
Iteration 5:{space 3}log likelihood = {res:-2039.6399}  
Iteration 6:{space 3}log likelihood = {res:-2039.6399}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     2,000
{txt}{col 49}LR chi2({res}7{txt}){col 67}= {res}   2287.70
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-2039.6399{txt}{col 49}Pseudo R2{col 67}= {res}    0.3593

{txt}{hline 26}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}MartialLawLimitsDemocracy{col 27}{c |}      Coef.{col 39}   Std. Err.{col 51}      z{col 59}   P>|z|{col 67}     [95% Con{col 80}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}PastMartialLawsJustified {c |}{col 27}{res}{space 2}-.5459144{col 39}{space 2} .0589182{col 50}{space 1}   -9.27{col 59}{space 3}0.000{col 67}{space 4} -.661392{col 80}{space 3}-.4304369
{txt}{space 22}Age {c |}{col 27}{res}{space 2} .0069753{col 39}{space 2} .0525034{col 50}{space 1}    0.13{col 59}{space 3}0.894{col 67}{space 4}-.0959295{col 80}{space 3}   .10988
{txt}{space 19}Gender {c |}{col 27}{res}{space 2}-.0378297{col 39}{space 2} .0863974{col 50}{space 1}   -0.44{col 59}{space 3}0.661{col 67}{space 4}-.2071656{col 80}{space 3} .1315062
{txt}{space 19}Income {c |}{col 27}{res}{space 2}-.1004982{col 39}{space 2} .0680554{col 50}{space 1}   -1.48{col 59}{space 3}0.140{col 67}{space 4}-.2338844{col 80}{space 3}  .032888
{txt}{space 16}Education {c |}{col 27}{res}{space 2} .0267816{col 39}{space 2}  .067655{col 50}{space 1}    0.40{col 59}{space 3}0.692{col 67}{space 4}-.1058197{col 80}{space 3} .1593829
{txt}{space 17}Religion {c |}{col 27}{res}{space 2}-.1262353{col 39}{space 2} .0984353{col 50}{space 1}   -1.28{col 59}{space 3}0.200{col 67}{space 4}-.3191651{col 80}{space 3} .0666944
{txt}{space 17}Position {c |}{col 27}{res}{space 2} 5.111963{col 39}{space 2} .2682139{col 50}{space 1}   19.06{col 59}{space 3}0.000{col 67}{space 4} 4.586274{col 80}{space 3} 5.637653
{txt}{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                    /cut1 {c |}{col 27}{res}{space 2}-3.518155{col 39}{space 2} .3571699{col 67}{space 4}-4.218195{col 80}{space 3}-2.818115
{txt}                    /cut2 {c |}{col 27}{res}{space 2} -1.68762{col 39}{space 2} .3547719{col 67}{space 4}-2.382961{col 80}{space 3}-.9922803
{txt}                    /cut3 {c |}{col 27}{res}{space 2} 1.198874{col 39}{space 2} .3954066{col 67}{space 4} .4238916{col 80}{space 3} 1.973857
{txt}                    /cut4 {c |}{col 27}{res}{space 2} 4.204266{col 39}{space 2} .3961039{col 67}{space 4} 3.427917{col 80}{space 3} 4.980616
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estimates store model_2

. 
. 
. 
. 
. 
. ologit MartialLawNecessaryforSecuri PastMartialLawsJustified Age Gender Income Education Religion Position

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-3120.0135}  
Iteration 1:{space 3}log likelihood = {res:-2176.8886}  
Iteration 2:{space 3}log likelihood = {res:-2034.6293}  
Iteration 3:{space 3}log likelihood = {res:-2023.3261}  
Iteration 4:{space 3}log likelihood = {res:-2023.2029}  
Iteration 5:{space 3}log likelihood = {res:-2023.2029}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     2,000
{txt}{col 49}LR chi2({res}7{txt}){col 67}= {res}   2193.62
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-2023.2029{txt}{col 49}Pseudo R2{col 67}= {res}    0.3515

{txt}{hline 29}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}MartialLawNecessaryforSecuri{col 30}{c |}      Coef.{col 42}   Std. Err.{col 54}      z{col 62}   P>|z|{col 70}     [95% Con{col 83}f. Interval]
{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}PastMartialLawsJustified {c |}{col 30}{res}{space 2}  .804962{col 42}{space 2} .0591661{col 53}{space 1}   13.61{col 62}{space 3}0.000{col 70}{space 4} .6889987{col 83}{space 3} .9209253
{txt}{space 25}Age {c |}{col 30}{res}{space 2}-.0387289{col 42}{space 2} .0536084{col 53}{space 1}   -0.72{col 62}{space 3}0.470{col 70}{space 4}-.1437994{col 83}{space 3} .0663416
{txt}{space 22}Gender {c |}{col 30}{res}{space 2} .0424093{col 42}{space 2} .0874129{col 53}{space 1}    0.49{col 62}{space 3}0.628{col 70}{space 4}-.1289169{col 83}{space 3} .2137355
{txt}{space 22}Income {c |}{col 30}{res}{space 2}-.0132649{col 42}{space 2} .0675967{col 53}{space 1}   -0.20{col 62}{space 3}0.844{col 70}{space 4}-.1457519{col 83}{space 3} .1192221
{txt}{space 19}Education {c |}{col 30}{res}{space 2} .0235963{col 42}{space 2} .0695009{col 53}{space 1}    0.34{col 62}{space 3}0.734{col 70}{space 4}-.1126229{col 83}{space 3} .1598155
{txt}{space 20}Religion {c |}{col 30}{res}{space 2}-.0886926{col 42}{space 2} .1019219{col 53}{space 1}   -0.87{col 62}{space 3}0.384{col 70}{space 4}-.2884558{col 83}{space 3} .1110706
{txt}{space 20}Position {c |}{col 30}{res}{space 2}-4.059417{col 42}{space 2} .2406503{col 53}{space 1}  -16.87{col 62}{space 3}0.000{col 70}{space 4}-4.531083{col 83}{space 3}-3.587751
{txt}{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                       /cut1 {c |}{col 30}{res}{space 2}-3.686263{col 42}{space 2} .3753176{col 70}{space 4}-4.421872{col 83}{space 3}-2.950654
{txt}                       /cut2 {c |}{col 30}{res}{space 2}-2.061339{col 42}{space 2} .3772473{col 70}{space 4} -2.80073{col 83}{space 3}-1.321948
{txt}                       /cut3 {c |}{col 30}{res}{space 2} .0624741{col 42}{space 2} .3799738{col 70}{space 4}-.6822609{col 83}{space 3} .8072091
{txt}                       /cut4 {c |}{col 30}{res}{space 2} 3.175033{col 42}{space 2} .3545069{col 70}{space 4} 2.480213{col 83}{space 3} 3.869854
{txt}{hline 29}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estimates store model_3

. 
. 
. 
. coefplot (model_1), bylabel ((a) DV: Position on impeachment) || (model_2), bylabel ((b) DV: Impact on democracy) || (model_3), bylabel ((c) DV: Unavoidable decision) ||, eform omitted xline(1, lcolor(black) lwidth(thin)) lpattern(dash) graphregion(fcolor(white)) mlabel format(%9.3f) mlabposition(8) mlabsize(tiny) level(95 90) ciopts(lwidth(*0.5 *2))  keep( PastMartialLawsJustified )
{res}
{com}. ologit DemocracyPriorityinCrisis PoliticalOrientation Age Gender Income Education Religion Position

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-3091.9325}  
Iteration 1:{space 3}log likelihood = {res:-2045.1017}  
Iteration 2:{space 3}log likelihood = {res:-1832.4389}  
Iteration 3:{space 3}log likelihood = {res:-1791.3728}  
Iteration 4:{space 3}log likelihood = {res:-1782.6805}  
Iteration 5:{space 3}log likelihood = {res:-1780.6571}  
Iteration 6:{space 3}log likelihood = {res:-1780.2242}  
Iteration 7:{space 3}log likelihood = {res:-1780.1349}  
Iteration 8:{space 3}log likelihood = {res:-1780.1145}  
Iteration 9:{space 3}log likelihood = {res:-1780.1094}  
Iteration 10:{space 2}log likelihood = {res:-1780.1084}  
Iteration 11:{space 2}log likelihood = {res:-1780.1083}  
Iteration 12:{space 2}log likelihood = {res:-1780.1082}  
Iteration 13:{space 2}log likelihood = {res:-1780.1082}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     2,000
{txt}{col 49}LR chi2({res}7{txt}){col 67}= {res}   2623.65
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1780.1082{txt}{col 49}Pseudo R2{col 67}= {res}    0.4243

{txt}{hline 26}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}DemocracyPriorityinCrisis{col 27}{c |}      Coef.{col 39}   Std. Err.{col 51}      z{col 59}   P>|z|{col 67}     [95% Con{col 80}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}PoliticalOrientation {c |}{col 27}{res}{space 2}-.2861556{col 39}{space 2} .0824847{col 50}{space 1}   -3.47{col 59}{space 3}0.001{col 67}{space 4}-.4478226{col 80}{space 3}-.1244886
{txt}{space 22}Age {c |}{col 27}{res}{space 2} .0033339{col 39}{space 2} .0540656{col 50}{space 1}    0.06{col 59}{space 3}0.951{col 67}{space 4}-.1026326{col 80}{space 3} .1093005
{txt}{space 19}Gender {c |}{col 27}{res}{space 2}-.0613884{col 39}{space 2} .0896982{col 50}{space 1}   -0.68{col 59}{space 3}0.494{col 67}{space 4}-.2371935{col 80}{space 3} .1144168
{txt}{space 19}Income {c |}{col 27}{res}{space 2}  .019292{col 39}{space 2} .0720382{col 50}{space 1}    0.27{col 59}{space 3}0.789{col 67}{space 4}-.1219004{col 80}{space 3} .1604843
{txt}{space 16}Education {c |}{col 27}{res}{space 2} .1172028{col 39}{space 2} .0688524{col 50}{space 1}    1.70{col 59}{space 3}0.089{col 67}{space 4}-.0177454{col 80}{space 3}  .252151
{txt}{space 17}Religion {c |}{col 27}{res}{space 2}-.0773873{col 39}{space 2} .1008725{col 50}{space 1}   -0.77{col 59}{space 3}0.443{col 67}{space 4}-.2750938{col 80}{space 3} .1203192
{txt}{space 17}Position {c |}{col 27}{res}{space 2} 23.52784{col 39}{space 2} 761.6546{col 50}{space 1}    0.03{col 59}{space 3}0.975{col 67}{space 4}-1469.288{col 80}{space 3} 1516.343
{txt}{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                    /cut1 {c |}{col 27}{res}{space 2}-1.471466{col 39}{space 2} .3326153{col 67}{space 4} -2.12338{col 80}{space 3}-.8195514
{txt}                    /cut2 {c |}{col 27}{res}{space 2} .2814143{col 39}{space 2} .3324267{col 67}{space 4}-.3701302{col 80}{space 3} .9329587
{txt}                    /cut3 {c |}{col 27}{res}{space 2} 19.65314{col 39}{space 2} 761.6546{col 67}{space 4}-1473.162{col 80}{space 3} 1512.469
{txt}                    /cut4 {c |}{col 27}{res}{space 2} 22.63184{col 39}{space 2} 761.6546{col 67}{space 4}-1470.184{col 80}{space 3} 1515.447
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estimates store model_4

. 
. 
. 
. ologit SecurityJustifiesFreedomLimit PoliticalOrientation Age Gender Income Education Religion Position

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-2900.1782}  
Iteration 1:{space 3}log likelihood = {res:-1912.1582}  
Iteration 2:{space 3}log likelihood = {res:-1765.1779}  
Iteration 3:{space 3}log likelihood = {res:-1747.5441}  
Iteration 4:{space 3}log likelihood = {res:-1747.1551}  
Iteration 5:{space 3}log likelihood = {res:-1747.1543}  
Iteration 6:{space 3}log likelihood = {res:-1747.1543}  
{res}
{txt}Ordered logistic regression{col 49}Number of obs{col 67}= {res}     2,000
{txt}{col 49}LR chi2({res}7{txt}){col 67}= {res}   2306.05
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-1747.1543{txt}{col 49}Pseudo R2{col 67}= {res}    0.3976

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}SecurityJustifiesFreedomLimit{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      z{col 63}   P>|z|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}PoliticalOrientation {c |}{col 31}{res}{space 2} 1.044778{col 43}{space 2} .0873046{col 54}{space 1}   11.97{col 63}{space 3}0.000{col 71}{space 4} .8736639{col 84}{space 3} 1.215892
{txt}{space 26}Age {c |}{col 31}{res}{space 2}-.0117434{col 43}{space 2} .0561547{col 54}{space 1}   -0.21{col 63}{space 3}0.834{col 71}{space 4}-.1218047{col 84}{space 3} .0983179
{txt}{space 23}Gender {c |}{col 31}{res}{space 2} .2217473{col 43}{space 2} .0918809{col 54}{space 1}    2.41{col 63}{space 3}0.016{col 71}{space 4} .0416641{col 84}{space 3} .4018304
{txt}{space 23}Income {c |}{col 31}{res}{space 2} .0235035{col 43}{space 2}    .0713{col 54}{space 1}    0.33{col 63}{space 3}0.742{col 71}{space 4}-.1162419{col 84}{space 3}  .163249
{txt}{space 20}Education {c |}{col 31}{res}{space 2} .0672398{col 43}{space 2} .0729471{col 54}{space 1}    0.92{col 63}{space 3}0.357{col 71}{space 4}-.0757339{col 84}{space 3} .2102135
{txt}{space 21}Religion {c |}{col 31}{res}{space 2} .2091485{col 43}{space 2} .1066003{col 54}{space 1}    1.96{col 63}{space 3}0.050{col 71}{space 4} .0002157{col 84}{space 3} .4180812
{txt}{space 21}Position {c |}{col 31}{res}{space 2}-5.145228{col 43}{space 2} .2566703{col 54}{space 1}  -20.05{col 63}{space 3}0.000{col 71}{space 4}-5.648292{col 84}{space 3}-4.642163
{txt}{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                        /cut1 {c |}{col 31}{res}{space 2}-4.434743{col 43}{space 2} .3888475{col 71}{space 4} -5.19687{col 84}{space 3}-3.672616
{txt}                        /cut2 {c |}{col 31}{res}{space 2} -1.48031{col 43}{space 2} .3954902{col 71}{space 4}-2.255457{col 84}{space 3}-.7051635
{txt}                        /cut3 {c |}{col 31}{res}{space 2}-.5626837{col 43}{space 2} .3900147{col 71}{space 4}-1.327098{col 84}{space 3} .2017311
{txt}                        /cut4 {c |}{col 31}{res}{space 2} 2.736843{col 43}{space 2} .3488613{col 71}{space 4} 2.053087{col 84}{space 3} 3.420598
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estimates store model_5

. 
. 
. 
. 
. 
. coefplot (model_4), bylabel ((a) DV: Democracy as the top priority) || (model_5), bylabel ((b) DV: Restrictions on civil liberties) ||, eform omitted xline(1, lcolor(black) lwidth(thin)) lpattern(dash) graphregion(fcolor(white)) mlabel format(%9.3f) mlabposition(8) mlabsize(tiny) level(95 90) ciopts(lwidth(*0.5 *2))  keep( PoliticalOrientation )
{res}
{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\research\works\주제45_계엄_탄핵_민주주의\democratization\data\code_q2_q3.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 4 May 2025, 23:56:50
{txt}{.-}
{smcl}
{txt}{sf}{ul off}